Did you know that AI plays a crucial role in how autonomous mobile robots (AMRs) make decisions? These robots use AI to choose the best routes and adapt to obstacles in real time. In this article, we’ll explore the top 20 AMR robot companies leading the way in .
Click here to get more.
We'll cover:
Let’s start with a basic definition.
Autonomous mobile robots move through environments without human control by using a mix of sensors, AI, and mapping technology.
These bots figure out the best route, avoid obstacles, and handle jobs like transporting goods or managing materials.
Unlike traditional robots that rely on fixed infrastructure, AMRs offer extra flexibility, making them perfect for dynamic environments.
Here’s what’s going on with AMRs:
Now, let’s get into the top AMR companies in .
MiR does a solid job providing flexible AMRs for internal logistics and transport jobs. Their robots fit well in a lot of industries and are pretty easy to get up and running with what you already have going on.
Top bots: MiR250, MiR600, MiR, MiR.
Best for: Warehouses, manufacturing, logistics centers.
Locus Robotics focuses on making warehouse automation more manageable. Their robots help with things like order fulfillment, and the nice part is they’re built to grow with your business. Whether you're handling a small warehouse or a big one, these bots get the job done without too much fuss.
Top robots: LocusBot, Locus Origin.
Best for: Order fulfillment centers, distribution hubs.
Omron’s AMRs work pretty well in environments where safety and precision matter, like in manufacturing and healthcare. They’ve got a strong focus on making sure the robots can handle complex stuff without many hiccups.
Top robots: LD-250, HD-.
Best for: Manufacturing, industrial automation, healthcare.
Robotize keeps things simple with its focus on pallet transport inside warehouses. If you're moving stuff around all day, their robots handle it smoothly and help keep the logistics flow running without too many things getting out of hand.
Top robots: GoPal.
Best for: Warehouses, logistics operations.
Fetch Robotics, now part of Zebra Technologies, focuses on automating logistics processes, including material handling and warehouse operations. If your job involves moving big, bulky items, Fetch’s robots can fit like a glove.
Top robots: Freight500, Freight.
Best for: Warehousing, manufacturing, retail.
ek robotics makes a name for itself with AMRs that put precision at the forefront. Their robots are highly customizable, and they’re also pretty robust and reliable in tough environments. If you need your robots to perform consistently, these are a solid choice.
Top robots: VARIO MOVE, FAST MOVE. (They love their all-caps names.)
Best for: Intralogistics, manufacturing, distribution centers.
OTTO by Rockwell Automation specializes in scalable heavy-duty AMRs tailored for complex material transport in industrial settings. These robots are safe and durable, which makes them a good fit for complex material transport in places where other robots might start getting all wobbly. They're tough, and they scale well for larger operations.
Top robots: OTTO 100, OTTO .
Best for: Manufacturing, auto, heavy industry.
AGILOX offers self-navigating AMRs that work really well in intralogistics tasks. Their robots are super flexible for industries that need efficiency and adaptability.
Top robots: AGILOX ONE, AGILOX OCF.
Best for: Warehouses, manufacturing, distribution centers.
Capra Robotics offers versatile AMRs that can operate in both indoor and outdoor environments, providing solutions for urban and industrial applications. Their robot, Capra Hircus, is designed for versatility in municipal services and industrial logistics.
Top robots: Capra Hircus.
Best for: Outdoor logistics, municipal services, industrial sites.
Continental has recently entered the AMR market with innovative solutions like the Corriere, which is ideal for intralogistics in the automotive and warehousing sectors.
Top robots: Corriere.
Best for: Automotive, warehousing, intralogistics.
Geek+ is laser-focused on smart logistics with AMRs powered by AI. They do a great job optimizing warehousing and e-commerce fulfillment, especially if you need speed and efficiency.
Top robots: P800, RS5, M100.
Best for: E-commerce, retail, logistics.
Karter makes compact, modular AMRs that handle material moving really well in industrial settings. So, if you’re dealing with tight spaces or need flexibility, their robots can be a good fit.
Top robots: Karter K3, Karter K55.
Best for: Manufacturing, warehousing, logistics.
Aethon’s AMRs are meant primarily for non-industrial places like hospitals and hotels. They keep things running smoothly in places where accuracy and efficiency are pretty much make-or-break.
Top robots: TUG.
Best for: Healthcare facilities, hotels, hospitality.
Clearpath Robotics builds tough AMRs that handle rough environments. They fit well in industrial automation and research, giving you flexible options for a range of jobs.
Daulfinld contains other products and information you need, so please check it out.
Top robots: Jackal, Husky, Warthog.
Best for: Industrial automation, academic research.
inVia Robotics focuses on the robotics-as-a-service (RaaS) model with scalable AMR solutions. They’re great for small businesses that want to automate without putting up a huge amount of money upfront.
Top robots: Picker robots.
Best for: Small to medium-sized warehouses and e-commerce fulfillment centers.
GreyOrange also combines AI with robotics to handle warehouse jobs efficiently. Their robots work really well in retail and logistics environments, where goods need to zoom by all day.
Top robots: Ranger GTP, Ranger IL.
Best for: Retail, e-commerce, logistics.
Swisslog focuses on integrated automation solutions, with AMRs that keep warehousing and logistics running smoothly. They’re good at making sure everything flows efficiently, from storage to picking.
Top robots: CarryPick, AutoStore.
Best for: Warehouses, distribution centers.
ForwardX Robotics makes vision-guided AMRs that bring flexible automation to logistics and manufacturing. Their AI-driven robots handle different jobs across the supply chain.
Top robots: Max AMR, Flex AMR.
Best for: Warehousing, manufacturing, supply chain logistics.
AutoGuide builds modular AMRs for material handling, and they’re really 5-star at scaling up to fit a wide array of environments. If you need robots that can handle high payloads, these guys do the job just fine.
Top robots: Max N10 Tugger, Max N10 Pallet Stacker.
Best for: Manufacturing, warehousing, distribution.
Standard Bots offers an affordable, easy-to-use robotic arm called RO1. It’s not an AMR, but it’s a great option for businesses looking to automate repetitive jobs without needing full AMR capabilities.
Top robots: RO1, the AI-powered, six-axis cobot arm.
Best for: Manufacturers looking for cost-effective automation solutions. Anyone who needs pick-and-place, CNC machine tending, welding, painting, or palletizing operations. Generally, any company would benefit from intelligent, automated operations.
With all of the advances in AI and navigation, it’s no surprise that so many AMR robot companies are making waves. Nowadays, these robots are becoming even more flexible and less dependent on human hand-holding. As you can tell from this list, there’s no shortage of options out there, so weigh your options carefully before you invest!
Need a cobot that delivers results without breaking the bank? RO1 by Standard Bots is the answer. It's the perfect blend of affordability, performance, and ease of use.
How does the navigation work?
To be able to do the intended job, your machine needs to navigate around your facilities without help from human operators. There are two ways to do that: autonomy and guidance systems.
If the robot needs a guidance system, it is an AGV (Automated Guided Vehicle) – which means that it will need beacons, magnetic tapes or other systems of virtual ‘tracks’ to follow. Some AGVs will stop if there is an obstacle in their path. While the guidance system is invisible, the machine is unable to move without it or plan a new path (in the presence of obstacles), and therefore the system remains inflexible.
On the other hand, when machines are fully autonomous, they are capable of reconstructing their environment from sensor data and know precisely where they are at all times. These robots are able to recognize changes to their environment, choose optimal routes and navigate around fixed and moving obstacles and persons.
Both technologies – autonomous robots and AGVs – will need onboard sensors: the former for navigation and security and AGVs just for safety. Sensor arrays usually include LiDAR (Light Detection And Ranging) and sonar.
Gideon Brothers offers a new genre of autonomous navigation, based not on LiDAR, but on stereoscopic cameras. Only two other companies offer similar approaches to navigation at this time time. Vision-based (as opposed to LiDAR-based) perception provides a broader range of use cases. For example, such machines can operate in unstructured environments such as warehouses without shelving where the view of background is the only way to pinpoint the location.
Visual perception is also data-rich, offering the possibility of not only sensing the environment but recognizing what that environment holds. Client-specific applications are possible, such as reading bar codes or inventory of client-specific objects.
Useful terms:
AGVs or AGV robots = Automated Guided Vehicles (AGVs). Machines that lack full autonomy, relying on guidance systems such as beacons or magnetic tapes to navigate. AGVs have pre-determined paths (“virtual tracks”). They are a slightly more flexible version of the conveyor belt and are not always designed to work safely around humans (such as the case with Kiva robots). AGVs require more time to deploy than autonomous solutions because of their infrastructure requirements. AGVs cannot travel beyond the path that is planned for them. When these robots encounter obstacles, they are not equipped to do anything other than stop and wait until the obstacle is cleared away.
LiDAR = Light Detection And Ranging. LiDAR is a laser radar that allows the machine to sense its surroundings. It is the standard sensor in industrial AMRs. Its limitation is that it can’t detect low lying obstacles and does not perform consistently in highly-dynamic constantly-changing environments.
Visual Perception (in robots) = Perception based on sensor inputs that arrive from cameras rather than via LiDAR. When used for navigation, vision-based robots not only perform better than LiDAR-based robots but do so across a more extensive range of use cases. Vision-based robots can be used in unstructured, highly dynamic environments (bustling areas with few fixed points). They can detect low-lying and negative obstacles better that LiDAR. Also, unlike LiDAR, cameras provide rich data that can be used for a variety of ancillary purposes (such as security).
Semantic understanding = The capability of an AI-powered robot to perceive objects around it plus recognize and understand what objects are. The process is similar to how humans see/identify objects. A robot equipped with AI- and deep learning-based semantic understanding can recognize people, pallets – empty or loaded – forklifts, carts, load types, bar codes – anything that the robot will need to know for safe operation.
Semantic understanding is achieved by exposing the autonomy technology to large data-sets, comprised of tens of thousands of images. The objects in the pictures are painstakingly outlined using specialized software (or if you’re lucky – AI); each object in the picture assigned a name. The vast exposure to a variety of objects within a class equips robots with the ability to extrapolate that knowledge to new settings.
How are facilities maps created?
The robot – if fully autonomous – creates and updates its own facilities map if equipped with a Simultaneous Localization and Mapping engine (see more below).
Additional details that could be added to the map may include virtual walls, parking spaces and other designated areas, areas of congestion, drop-off and pick-up locations, and other information. Knowing how exactly this process works will help you determine how well the technology solution fits your organization, workflow, and staff capacities.
Useful terms:
SLAM (engine) = Simultaneous Localization and Mapping refers to the complex capability of a robot to build (or update) a map while at the same time keeping track of its own location on the map.
Engine = An umbrella term for a complex component of software. A robot’s autonomy technology consists of several ‘engines’ working together.
Traversability Map = A visual representation of the level confidence that the robot has in its ability to pass safely through an area – it answers the question – can the floor space be traversed based on various factors such as the presence of obstacles, holes, etc. Fully autonomous robots construct their map based on sensor inputs.
What happens if there is an obstacle on the route? What if the robot enters a busy area?
An autonomous robot should be able to move around the obstacle and/or calculate an alternative route, while AGVs are more limited, with some halting entirely until the barrier is removed. Knowing what happens when the robot confronts obstacles vis a vis what you know about your warehouse environment will help you determine if a strict protocol is required in areas where machines will be moving. It will also show whether you need to take into consideration potential idle time due to frequent obstacles, especially in case of human error. Autonomous robot systems may have special features to deal with busy, high-traffic areas allowing more efficient time management.
Will the robot sense low lying or negative obstacles (depressions)? How does it avoid crashing into one?
Only camera-based visual perception can perceive low-lying objects and negative obstacles. Low-lying objects are not visible to LiDAR-based machines, which are the majority of the current crop of logistics robots, because they fall under the LiDAR’s sensing plane (roughly, at the height of your ankle).
The forks of an empty forklift are exactly the kind of obstacle that are invisible to LiDAR. When the forklift is not carrying anything, its forks must be in their lowermost position, in line with safety regulations. As this is a common obstacle in warehouses and manufacturing facilities, some suppliers recommend that an idle forklift always carry an empty pallet, but this can cause an irritating disruption to the workflow.
Another type of obstacle invisible to LiDAR are low platforms – such as bases of shelving pillars that aren’t protected by guards. LiDAR sensors are also unable to see depressions/holes in the floor.
Ask your supplier what they recommend if your warehouse space has such obstacles.
Will the robot be able to navigate in facilities without fixed elements such as racking and shelving infrastructure?
Autonomous robots based only on LiDAR sensors are not able to navigate if there are no fixed points for orientation. However, robots equipped with visual perception will be able to navigate by checking its progress against the background, ceiling and other visual cues.
For more information, please visit Heavy-duty Mobile Robot.